SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

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Showing 741–750 of 3874 papers

TitleStatusHype
Learned Compression for Images and Point CloudsCode1
Learned Image Downscaling for Upscaling using Content Adaptive ResamplerCode1
DDistill-SR: Reparameterized Dynamic Distillation Network for Lightweight Image Super-ResolutionCode1
Discovering Distinctive "Semantics" in Super-Resolution NetworksCode1
CutMIB: Boosting Light Field Super-Resolution via Multi-View Image BlendingCode1
Adaptive Convolutional Neural Network for Image Super-resolutionCode1
CVAE-GAN: Fine-Grained Image Generation through Asymmetric TrainingCode1
A heterogeneous group CNN for image super-resolutionCode1
A Text Attention Network for Spatial Deformation Robust Scene Text Image Super-resolutionCode1
DL4DS -- Deep Learning for empirical DownScalingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified